View Javadoc

1   /*
2    * Licensed to the Apache Software Foundation (ASF) under one or more
3    * contributor license agreements.  See the NOTICE file distributed with
4    * this work for additional information regarding copyright ownership.
5    * The ASF licenses this file to You under the Apache License, Version 2.0
6    * (the "License"); you may not use this file except in compliance with
7    * the License.  You may obtain a copy of the License at
8    *
9    *      http://www.apache.org/licenses/LICENSE-2.0
10   *
11   * Unless required by applicable law or agreed to in writing, software
12   * distributed under the License is distributed on an "AS IS" BASIS,
13   * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14   * See the License for the specific language governing permissions and
15   * limitations under the License.
16   */
17  package org.apache.commons.math3.stat.descriptive.moment;
18  
19  import java.io.Serializable;
20  
21  import org.apache.commons.math3.exception.MathIllegalArgumentException;
22  import org.apache.commons.math3.exception.NullArgumentException;
23  import org.apache.commons.math3.stat.descriptive.AbstractStorelessUnivariateStatistic;
24  import org.apache.commons.math3.stat.descriptive.WeightedEvaluation;
25  import org.apache.commons.math3.stat.descriptive.summary.Sum;
26  import org.apache.commons.math3.util.MathUtils;
27  
28  /**
29   * <p>Computes the arithmetic mean of a set of values. Uses the definitional
30   * formula:</p>
31   * <p>
32   * mean = sum(x_i) / n
33   * </p>
34   * <p>where <code>n</code> is the number of observations.
35   * </p>
36   * <p>When {@link #increment(double)} is used to add data incrementally from a
37   * stream of (unstored) values, the value of the statistic that
38   * {@link #getResult()} returns is computed using the following recursive
39   * updating algorithm: </p>
40   * <ol>
41   * <li>Initialize <code>m = </code> the first value</li>
42   * <li>For each additional value, update using <br>
43   *   <code>m = m + (new value - m) / (number of observations)</code></li>
44   * </ol>
45   * <p> If {@link #evaluate(double[])} is used to compute the mean of an array
46   * of stored values, a two-pass, corrected algorithm is used, starting with
47   * the definitional formula computed using the array of stored values and then
48   * correcting this by adding the mean deviation of the data values from the
49   * arithmetic mean. See, e.g. "Comparison of Several Algorithms for Computing
50   * Sample Means and Variances," Robert F. Ling, Journal of the American
51   * Statistical Association, Vol. 69, No. 348 (Dec., 1974), pp. 859-866. </p>
52   * <p>
53   *  Returns <code>Double.NaN</code> if the dataset is empty.
54   * </p>
55   * <strong>Note that this implementation is not synchronized.</strong> If
56   * multiple threads access an instance of this class concurrently, and at least
57   * one of the threads invokes the <code>increment()</code> or
58   * <code>clear()</code> method, it must be synchronized externally.
59   *
60   * @version $Id: Mean.java 1416643 2012-12-03 19:37:14Z tn $
61   */
62  public class Mean extends AbstractStorelessUnivariateStatistic
63      implements Serializable, WeightedEvaluation {
64  
65      /** Serializable version identifier */
66      private static final long serialVersionUID = -1296043746617791564L;
67  
68      /** First moment on which this statistic is based. */
69      protected FirstMoment moment;
70  
71      /**
72       * Determines whether or not this statistic can be incremented or cleared.
73       * <p>
74       * Statistics based on (constructed from) external moments cannot
75       * be incremented or cleared.</p>
76       */
77      protected boolean incMoment;
78  
79      /** Constructs a Mean. */
80      public Mean() {
81          incMoment = true;
82          moment = new FirstMoment();
83      }
84  
85      /**
86       * Constructs a Mean with an External Moment.
87       *
88       * @param m1 the moment
89       */
90      public Mean(final FirstMoment m1) {
91          this.moment = m1;
92          incMoment = false;
93      }
94  
95      /**
96       * Copy constructor, creates a new {@code Mean} identical
97       * to the {@code original}
98       *
99       * @param original the {@code Mean} instance to copy
100      * @throws NullArgumentException if original is null
101      */
102     public Mean(Mean original) throws NullArgumentException {
103         copy(original, this);
104     }
105 
106     /**
107      * {@inheritDoc}
108      * <p>Note that when {@link #Mean(FirstMoment)} is used to
109      * create a Mean, this method does nothing. In that case, the
110      * FirstMoment should be incremented directly.</p>
111      */
112     @Override
113     public void increment(final double d) {
114         if (incMoment) {
115             moment.increment(d);
116         }
117     }
118 
119     /**
120      * {@inheritDoc}
121      */
122     @Override
123     public void clear() {
124         if (incMoment) {
125             moment.clear();
126         }
127     }
128 
129     /**
130      * {@inheritDoc}
131      */
132     @Override
133     public double getResult() {
134         return moment.m1;
135     }
136 
137     /**
138      * {@inheritDoc}
139      */
140     public long getN() {
141         return moment.getN();
142     }
143 
144     /**
145      * Returns the arithmetic mean of the entries in the specified portion of
146      * the input array, or <code>Double.NaN</code> if the designated subarray
147      * is empty.
148      * <p>
149      * Throws <code>IllegalArgumentException</code> if the array is null.</p>
150      * <p>
151      * See {@link Mean} for details on the computing algorithm.</p>
152      *
153      * @param values the input array
154      * @param begin index of the first array element to include
155      * @param length the number of elements to include
156      * @return the mean of the values or Double.NaN if length = 0
157      * @throws MathIllegalArgumentException if the array is null or the array index
158      *  parameters are not valid
159      */
160     @Override
161     public double evaluate(final double[] values,final int begin, final int length)
162     throws MathIllegalArgumentException {
163         if (test(values, begin, length)) {
164             Sum sum = new Sum();
165             double sampleSize = length;
166 
167             // Compute initial estimate using definitional formula
168             double xbar = sum.evaluate(values, begin, length) / sampleSize;
169 
170             // Compute correction factor in second pass
171             double correction = 0;
172             for (int i = begin; i < begin + length; i++) {
173                 correction += values[i] - xbar;
174             }
175             return xbar + (correction/sampleSize);
176         }
177         return Double.NaN;
178     }
179 
180     /**
181      * Returns the weighted arithmetic mean of the entries in the specified portion of
182      * the input array, or <code>Double.NaN</code> if the designated subarray
183      * is empty.
184      * <p>
185      * Throws <code>IllegalArgumentException</code> if either array is null.</p>
186      * <p>
187      * See {@link Mean} for details on the computing algorithm. The two-pass algorithm
188      * described above is used here, with weights applied in computing both the original
189      * estimate and the correction factor.</p>
190      * <p>
191      * Throws <code>IllegalArgumentException</code> if any of the following are true:
192      * <ul><li>the values array is null</li>
193      *     <li>the weights array is null</li>
194      *     <li>the weights array does not have the same length as the values array</li>
195      *     <li>the weights array contains one or more infinite values</li>
196      *     <li>the weights array contains one or more NaN values</li>
197      *     <li>the weights array contains negative values</li>
198      *     <li>the start and length arguments do not determine a valid array</li>
199      * </ul></p>
200      *
201      * @param values the input array
202      * @param weights the weights array
203      * @param begin index of the first array element to include
204      * @param length the number of elements to include
205      * @return the mean of the values or Double.NaN if length = 0
206      * @throws MathIllegalArgumentException if the parameters are not valid
207      * @since 2.1
208      */
209     public double evaluate(final double[] values, final double[] weights,
210                            final int begin, final int length) throws MathIllegalArgumentException {
211         if (test(values, weights, begin, length)) {
212             Sum sum = new Sum();
213 
214             // Compute initial estimate using definitional formula
215             double sumw = sum.evaluate(weights,begin,length);
216             double xbarw = sum.evaluate(values, weights, begin, length) / sumw;
217 
218             // Compute correction factor in second pass
219             double correction = 0;
220             for (int i = begin; i < begin + length; i++) {
221                 correction += weights[i] * (values[i] - xbarw);
222             }
223             return xbarw + (correction/sumw);
224         }
225         return Double.NaN;
226     }
227 
228     /**
229      * Returns the weighted arithmetic mean of the entries in the input array.
230      * <p>
231      * Throws <code>MathIllegalArgumentException</code> if either array is null.</p>
232      * <p>
233      * See {@link Mean} for details on the computing algorithm. The two-pass algorithm
234      * described above is used here, with weights applied in computing both the original
235      * estimate and the correction factor.</p>
236      * <p>
237      * Throws <code>MathIllegalArgumentException</code> if any of the following are true:
238      * <ul><li>the values array is null</li>
239      *     <li>the weights array is null</li>
240      *     <li>the weights array does not have the same length as the values array</li>
241      *     <li>the weights array contains one or more infinite values</li>
242      *     <li>the weights array contains one or more NaN values</li>
243      *     <li>the weights array contains negative values</li>
244      * </ul></p>
245      *
246      * @param values the input array
247      * @param weights the weights array
248      * @return the mean of the values or Double.NaN if length = 0
249      * @throws MathIllegalArgumentException if the parameters are not valid
250      * @since 2.1
251      */
252     public double evaluate(final double[] values, final double[] weights)
253     throws MathIllegalArgumentException {
254         return evaluate(values, weights, 0, values.length);
255     }
256 
257     /**
258      * {@inheritDoc}
259      */
260     @Override
261     public Mean copy() {
262         Mean result = new Mean();
263         // No try-catch or advertised exception because args are guaranteed non-null
264         copy(this, result);
265         return result;
266     }
267 
268 
269     /**
270      * Copies source to dest.
271      * <p>Neither source nor dest can be null.</p>
272      *
273      * @param source Mean to copy
274      * @param dest Mean to copy to
275      * @throws NullArgumentException if either source or dest is null
276      */
277     public static void copy(Mean source, Mean dest)
278         throws NullArgumentException {
279         MathUtils.checkNotNull(source);
280         MathUtils.checkNotNull(dest);
281         dest.setData(source.getDataRef());
282         dest.incMoment = source.incMoment;
283         dest.moment = source.moment.copy();
284     }
285 }